SREBP modulates the NADP+/NADPH cycle to control night sleep in Drosophila

Sleep behavior is conserved throughout evolution, and sleep disturbances are a frequent comorbidity of neuropsychiatric disorders. However, the molecular basis underlying sleep dysfunctions in neurological diseases remains elusive. Using a model for neurodevelopmental disorders (NDDs), the Drosophila Cytoplasmic FMR1 interacting protein haploinsufficiency (Cyfip85.1/+), we identify a mechanism modulating sleep homeostasis. We show that increased activity of the sterol regulatory element-binding protein (SREBP) in Cyfip85.1/+ flies induces an increase in the transcription of wakefulness-associated genes, such as the malic enzyme (Men), causing a disturbance in the daily NADP+/NADPH ratio oscillations and reducing sleep pressure at the night-time onset. Reduction in SREBP or Men activity in Cyfip85.1/+ flies enhances the NADP+/NADPH ratio and rescues the sleep deficits, indicating that SREBP and Men are causative for the sleep deficits in Cyfip heterozygous flies. This work suggests modulation of the SREBP metabolic axis as a new avenue worth exploring for its therapeutic potential in sleep disorders.

The link between Men expression and the NADP/NADPH pool may need to be further substantiated. The authors show that the ratios of NADP+/NADPH are altered in the Cyfip haploinsufficient flies and that these ratios are known to affect sleep pressure. Whilst the authors have shown genetic interactions between Srebp > Cyfip and Men > Cyfip they don't show the acute control of the NADP+/NADPH by Men in either of these backgrounds. Regarding the Betulin drug provision experiments, the method of administration was monitored via consumption of the drug mixed into blue food. However, there is no quantification of how much food was digested, or if the drug was found in the (relevant areas of the) brain. Figure 2b (the 24hr profile for NADP+/NADPH ratios, in mutants vs control) is key to this study. Unfortunately, the it is also one of the less believable graphs. The difference between the mutant and controls depends on one point, where significance seems marginal. That the 16hr timepoint happens to match the timepoint showing decreased nighttime sleep in the mutant could be viewed as coincidental. I wonder if there are additional approaches that could be taken to validate this result? Additionally, regarding the immunohistochemical experiments, were brain dissections done at a specific time of the day? If SREBP levels change throughout the course of 24 hours (peak expression at ZT12-ZT16) all dissections would need to be completed at a specific set time to account for circadian variation. Whether this was accounted for is unclear. Starvation leads to sleep loss as well; this is well documented in the field, and is obviously related to metabolism homeostatic processes as well. Have the authors excluded the possibility that they are actually describing one aspect of that well-described phenomenon? In other words, all cells might experience NADP+/NADPH ratio changes after extended wakefulness, and these might be reversed upon starvation conditions. Is it possible this has less to do with sleep than more general brain processes linked to hunger, with the mutant animals investigated here being simply more hungry at the start of the night (hence, not sleeping)? It's not clear that this has been ruled out or even considered.
Minor concerns and suggestions Figure 1a -a Schematic would be helpful to the reader to follow experimental setup. Figure 1b -Total max of nighttime sleep should be 720 minutes Figure 3 and generally seq data -Further explain the rationale behind using a cutoff fold change of +/-1.3 as the standard method is to use is Log2FC of 0.58 = LogFold of 1.5. Whilst the authors do state that this was due to a FC of 1.3 of Cyfip gene this may need to be detailed more? Figure 3b could be more informative, e.g. showing some raw seq reads. Figure 4d -The authors have used fluorescent intensity and whilst confocal settings are kept consistent, how have they accounted for background intensity? Extended figure 2d/e -When comparing the data of 2d and 2e some disparities are seen. Cyfip knockdown in RepoGal4 looks (*) more significant than in R23e10Gal4. Some differences in panel d seem as large as in e, yet none are significant in d. This seems suspect. Could this be due to the statistical testing as the former also includes the Nrv-Gal4 dataset, so simply a problem of multiple comparisons? Secondly The UAS-Cyfip-IR controls differ between the datasets. Finally, there is no quantification of these knockdowns. Extended Figure 2F -Which UAS-Cyfip-IR line was used? Methods: Sleep-Wake activity assays -light as an arousal stimulus is unusual, as it interferes wit the circadian clock. This might need some discussion, to address concerns that circadian factors aren't at play here. It would also be interesting to know how many flies were not responding to this stimulus. Fig. 5: in the concluding model (panel d) the authors seem to imply a daytime sleep effect, as well as a night time effect (increased NADP+/NADPH ratio leads to low sleep drive during both day and night). Yet, this is not what is proposed in the title and abstract and discussion. The authors might need to rethink their effects on daytime sleep, and this included showing all the daytime sleep data so to that readers can see the extent to which day and night sleep correlate in these manipulations. This is critical, because without the word 'night' in the title, the story packs somewhat less of a punch.
Reviewer #2 (Remarks to the Author): Mariano et al. use a previously established Drosophila model for neurodevelopmental disease to investigate the molecular mechanisms underlying sleep dysregulation in these disorders. They study flies that have a 50% reduction in Cyfip, a protein implicated in various neuropsychiatric disorders. Their data suggest that Cyfip inhibits SREBP which in turn upregulates malic enzyme. Thus, a reduction in Cyfip is proposed to enhance SREBP and malic enzyme levels, which then increase the NADPH/NADP ratio, resulting in a putative decrease in the metabolic drive for sleep. In general, the work is solid, especially the links between Cyfip, SREBP, and malic enzyme, and the functional connection between lipid metabolism and sleep regulation is interesting and potentially important. However, there are questions about whether the observed behavioral phenotypes are specifically related to sleep homeostasis, which could limit the novelty of the findings.
1. The sleep phenotypes observed may not reflect defects in sleep homeostasis. For example, in Figures 1D-1E, the data show that Cyfip hets are hyperaroused, which could account for the reduced baseline sleep and decreased recovery sleep after deprivation. Do levels or activity of Cyfip, malic enzyme, or SREBP vary according to sleep need? 2. It is not clear that Cyfip hets lack an increase of NADP/NADPH around dusk. The data appear to show an increase, but just earlier, from ZT8 to ZT12. Also, if the NADP/NADPH ratio reflects sleep need, then one would expect the peak to be ZT12, not ZT16, since animals would be sleeping from ZT12-16, which should lower sleep need. 3. In Cyfip hets and in a number of other manipulations, there is a suggestion of a rightward shift of both daytime and nighttime sleep. It would be helpful if the authors performed locomotor analyses in constant darkness to assess whether there are underlying circadian defects. 4. Fig S2--To support the notion that reduction of Cyfip levels affect sleep, the authors use 2 different RNAi lines crossed to ras2-Gal4. It is unclear why the authors chose here and in Figure 4 to use ras2-Gal4, as published literature suggests that it labels both non-neuronal and neuronal cells. These experiments should be repeated with nsyb-Gal4 or elav-Gal4. Also, the authors should show the sleep profile traces for the experiments in Figure S2-does knockdown of Cyfip show a similar decrease in early night sleep seen in Cyfip/+ flies? 5. Fig S2-they suggest that the effects of Cyfip knockdown on sleep can be localized to the ExFl2 neurons. To strengthen this potential mechanism, they should show knockdown of SREBP and malic enzyme in the ExFl2 neurons as well.
Minor comments: 1. Page 3, line 2, provide citation for sleep being conserved from worms to humans. 2. Figure 1E, it is unusual to examine recovery sleep after sleep deprivation during the night, when sleep is already high. The authors do examine recovery sleep during the daytime after 12 hr of sleep deprivation in Figure S2. Recommend moving the panel from Figure S2 to the main figures, and Figure  1E to the supplemental figures. 3. The authors should specify how many times the transgenic lines were backcrossed into their control background strain. 4. Can the authors comment on the marked expression of the SREBP reporter in ellipsoid body ring? 5. Genotypes are sometimes ambiguous. For example in Figure 5, Cyfip/SREBP animals-are these homozygous or heterozygous for the SREBP allele? 6. For tubGal80ts experiments, the authors state in the methods that they subject the flies to 29 deg for 3 days. Which days did they use for their baseline sleep recording? 7. Figure S2E-"R23E18" should be "R23E10" 7. The discussion is somewhat meandering. Recommend tightening this section.
Reviewer #3 (Remarks to the Author): By characterising the sleep profile of Cyfip haploinsufficiency mutants, Mariano and coauthors identified a novel and original mechanism underlying the regulation of sleep homeostasis in flies. Using a series of complementary and elegant experiments, the authors convincingly find that the activity of the master regulator of lipogenesis SREBP is upregulated in Cyfip mutants, causing the upregulation of lipogenic genes, and, in turn, nighttime sleep defects via an imbalance of the NADP+/NADPH ratio. These findings are highly relevant to the field. I recommend publication in Nature Communications provided that the authors address the major and minor points raised below.
Major points: 1) Figure 2b. It looks like the NADP+/NADPH ratio oscillates in a circadian-dependent manner following the sleep pattern of the flies and not in a sleep need-dependent manner (as correctly stated in the abstract but not in the main text). Otherwise, why would the NADP+/NADPH start increasing when the flies are asleep, i.e. when sleep need is being dissipated, and not when sleep need is highest, i.e. at the end the 12-hour day period (ZT8-12)? Even though it is an interesting hypothesis, I do not think that the authors can causally link the changes in NADP+/NADPH ratio to the regulation of nighttime sleep and in particular sleep homeostasis. To address the latter, they would need to show that the NADP+/NADPH ratio is differentially modulated after sleep deprivation (by compared sleepdeprived versus rested flies) in WT versus mutant flies. In addition, the authors should carefully rephrase the interpretation of the NADP+/NADPH ratio results.
2) Using a series of complementary and elegant experiments, the authors convincingly show that the master regulator of lipogenesis SREBP is unregulated in Cyfip mutants. What about the defects in sleep homeostasis shown in Extended Data Figure 2g and Figure 1e? Can they be rescued upon decreasing the expression of SREBP? Moreover, does neuronal SREBP expression block synaptic homeostasis? This should be addressed in the paper.
3) The images shown in Figure 4d are very difficult to quantify and to interpret due to the low signalto-noise ratio. Looking at the pictures, it seems that the fluorescence signal is higher in WT than mutant 'ring neurons' for example (it is visible from the pictures that SREBP is active in a subpopulation of ring neurons). Yet, the 'background' (or neuropil or SREBP?) signal is much higher in mutant than WT brains and quantifying this signal without correcting for background or without attributing it to neuronal expression might lead to wrong conclusions. One way to circumvent this problem would simply be to stain for GFP (instead of doing live imaging) and additionally to counterstain the neuropil with anti-Bruchpilot for example. This would not only amplify the signal and improve the signal-to-noise ratio but it would also allow to do ratiometric imaging and to correct, e.g., for background noise or antibody penetration. Without these changes, the results shown in Figure 4d are not conclusive. 4) In Kanellopoulos et al, the same lab found a higher mitochondrial activity in the Cyfip mutant brain. This led to a redistribution of the GABA pool from synaptic vesicles into the mitochondria, thereby dampening GABAergic synaptic transmission, which, in turn, had severe effects on the social behaviour and locomotor activity of mutant flies. In the same paper, the authors also showed that the social deficits but not the locomotor activity could be rescued by decreasing mitochondrial activity or increasing GABA levels. I am surprised that the authors did not follow up on this finding in the context of sleep. It would be interesting to know whether similar manipulations as used in Kanellopoulos et al can also rescue the effects on nighttime sleep and sleep homeostasis observed in Cyfip mutants. If not, it might be very intriguing that the same protein might affect different types of behaviour (social behaviour and sleep) via entirely different metabolic mechanisms and possibly different neuronal substrates.

5)
In Kanellopoulos et al, the same lab mapped the effect of Cyfip mutant protein onto specific GABAergic neurons. It would be interesting to know whether, e.g., knocking down Cyfip in these subsets of GABAergic neurons has an effect on sleep? 6) Page 8, line 12 & page 15, line 6: based on the sleep deprivation experiments and the NADP+/NADPH results, the authors propose that the mutants show a lower need for sleep. Yet, how do they reconcile this claim with the fact that the mutants show defects in associative learning (Woo et al (2019, Biol Psychiatry), a hallmark of cognitive defects due to sleep deprivation? Couldn't it also be that the sleep homeostasis machinery is defect, resulting in a reduction of homeostatic sleep?
Minor points: 1) Typo in Extended Data Figure 2e: third group from the left should be 'R23E10' instead of R23E18'.
2) In Extended Data Figure 2f, some, e.g., 'Mai179Gal4', but not all of the Gal4 names are written in italic characters. The same applies to other figures throughout the nomenclature. Could the authors homogenize the nomenclature?
3) Page 12, Line 24/25: does this imply that the malic enzyme is only over-active at ZT16 or regulated in a circadian-dependent manner? Based on the previously published proteomics results it doesn't seem to be the case. It would be informative if the authors would comment on that. In this manuscript, Mariano et al provide an interesting and thorough description of a sleep phenotype associated with the Cyfip gene and its epistatic pathway. The authors show that cyfip mutant heterozigous flies have a short-sleep nocturnal phenotype and possible homeostatic misregulation and they propose that upregulation of SREBP and Men are responsible for this phenotype. The work features an impressive amount of work, generally well-controlled and well presented. I personally do not like the overly translational approach in the manuscript, insisting over and over again on possible links with human disease that may or may not exist; I think the manuscript ultimately suffers from adopting this approach and the findings end up being secondary but I recognise this may be the authors' style and they are entitled to use whichever style they prefer.
Overall, I think the work is solid and self-standing and I do not have any requests for further experiments. I only have some minor suggestions/requests mostly regarding data presentation and wording of the conclusions: 1. The term haploinsufficient refers to genes, not to animals. The use of "haploinsufficient flies" (e.g. line 3 pg5) is technically inappropriate. The flies are heterozygous for the gene mutation whilst the gene is haploinsufficient.
2. An EEG/MRI abnormality is not a "sleep disturbance" (line 12 pg 4). It may in some cases correlate with one but a change in EEG pattern is not a disturbance per se.
3. In the figures, please add more information regarding the number of animals used. Figure 1a-c, for instance, says the n is 75 without specifying the n for each condition. Is it 75 per condition or overall? 4. Replace all bar plots (such as the ones in fig 1bc,d) with something statistically more appropriate showing the actual distribution of data (as you do for instance in 1e).
5. Some plots have dots as values but no indication of what they represent. For instance, I assume the dots in the rightmost panel of 1e or in 4e represent outliers while the dots in 2a or 4c are actual data points? It would be good to stick to more consistent data visualisation.
6. Do you have any information regarding the expression pattern of Cyfip in the adult brain? Schenck et al characterised its expression during development but what about adulthood? The results in Fig. 4d suggest its expression (or at least its action on SREBP) is limited to the ellipsoid bodies and that is confirmed by the 23E10 KD experiment but do you know if the gene is expressed anywhere else? I am asking because of the results in fig.2 and fig 5b which do not seem really compatible with a very localised expression of the gene. If you do have data about cyfip expression please show it. If you do not have those data and do not want to obtain them please add some caveats/discussion regarding the results in fig. 2 and 5. I am just quite surprised that a change in enzymatic activities in only a few neurons can be picked up doing biochemical assays in the whole brain. 7. Please provide more details regarding the statistical analysis used to study the overlap of genes shown in fig. 3 and discussed on pg 9. A hypergeometric distribution is mentioned in the figure legend without further details. Was the same analysis done for the data in figure 4a? with what significance? 8. The epistatic experiments shown in fig. 5 are very nice but the only evidence that Men is involved with this process is coming from the one experiment shown in fig. 5c and 5b. While suggestive, I am not convinced this is enough evidence for such a definitive claim. I recommend using a more cautious approach in your conclusions. 9. On the same line: please amend the title to be more accurate in its description. "drives" and "control" are two very strong words for something that affects only a relatively small part of the phenotype.
Revised Suppl. Table 1: Previous Suppl. Table 5 is now Table 1 In addition, we provide New Suppl. Data 5 and 6: dataset analysis on the RNA-seq and detailed statistics.

Reviewer #1 (Remarks to the Author):
Mariano et al, present an interesting article proposing a mechanism modulating sleep homeostasis, specifically night-time sleep. They show that upon activation of the sterol regulatory element-binding protein (SREBP) in a Drosophila model of neurodevelopment disorders, Cyfip, there is a transcriptional upregulation of genes known to be involved in lipid homeostasis. They focused on a couple of genes related to this, including malic enzyme (Men). An increase in Men activity is known to regulate the cycling of NADP+/NADPH levels, which have been linked in other work (from the Miesenbock lab) to sleep pressure. They demonstrate that alterations in this ratio, driven by lipid metabolism, are involved in regulating sleep pressure. In this way they have provided another link between the sleep state and the role metabolic changes have in controlling sleep processes. This is a solid piece of work that contributes important new knowledge to this rapidly developing field. Additionally, there is a growing realisation that not all sleep is equivalent in flies, and the findings presented here point to a role for metabolic pathways in night-time sleep (as opposed to daytime sleep). The paper is overall well-written and easy to follow, and the data are largely consistent. There are some issues however that the authors should consider, as well as more minor suggestions that might need to be attended to.
We appreciate the reviewer's positive comments on our work and performed the suggested experiments that helped to improve our manuscript. We hope that he/she is pleased with the new datasets included in the revised version of the manuscript.

Major points:
1) The authors make a major case about molecular pathways regulating night sleep specifically (starting with their title), but after presenting some daytime sleep comparisons early on, they neglect to show daytime sleep results for many of their genetic and pharmacological manipulations (e.g., Fig  4e-h, extended data Figure 2). These data exits, so the authors should show it. The prediction would be no effects on day sleep, anywhere. If this is not uniformly the case in their experiments, they should speculate why not. More broadly, more discussion might be needed to help readers understand why daytime sleep would not be subject metabolic regulatory processes. The authors begin the paper by bringing up this interesting day/night sleep dichotomy, but after having established it in one mutant do little to return to this problem, which should be relevant to all of their conditions. We thank the reviewer for suggesting to further dissect the day/night sleep dichotomy. In the revised version of the paper, in addition to the analysis of the night-time sleep amount, we have determined the daytime sleep (Suppl. Additionally, we added the following paragraph in the discussion: "In flies, night-time differs from daytime sleep 80 . The arousal threshold is higher at night compared to daytime, suggesting that night-time sleep might be associated with sleep homeostasis 80 . Remarkably, only a few genetic factors and mechanisms have been so far identified as regulators of daytime and night-time sleep 81 ". Please find below the new data included in the revised manuscript. Supplementary Fig. 2e, Day sleep amount in Ras2Gal4;TubGal80 ts/+ (n = 48), UAS-Cyfip-IR 1/+ (n = 15), Ras2Gal4;TubGal80 ts > UAS-Cyfip-IR 1 (n = 18), UAS-Cyfip-IR 2/+ (n = 21) and Ras2Gal4;TubGal80 ts > UAS-Cyfip-IR 2 (n = 31). One-way ANOVA, Sidak's multiple comparison test, *p < 0.05, **p < 0.01, ***p < 0.001 and ****p < 0.0001, n.s. = not significant. 2) The link between Men expression and the NADP/NADPH pool may need to be further substantiated. The authors show that the ratios of NADP+/NADPH are altered in the Cyfip haploinsufficient flies and that these ratios are known to affect sleep pressure. Whilst the authors have shown genetic interactions between Srebp > Cyfip and Men > Cyfip they don't show the acute control of the NADP+/NADPH by Men in either of these backgrounds. We agree with reviewer's comment that is important to further validate the link between Men and NADP + /NADPH. We therefore performed an independent, more specific, and more sensitive assay: targeted mass spectrometry (Hydrophilic Interaction Liquid Chromatography coupled to tandem mass spectrometry, HILIC-MS/MS) to detect with the NADP ratio in Men and Srebp mutant flies.
The mass spec analysis in the Cyfip 85.1 /Srebp 189 fly heads shows a partial rescue (increase) of the NADP + /NADPH ratio. The analysis in the Srebp 189/+ fly heads shows an increase (tendency) of the NADP + /NADPH ratio (p = 0.054) indicating an effect of Srebp on this molecular pathway. We decided to replace the former Fig. 5a obtained using the kit Colorimetric NADP + /NADPH kit from Abcam with the new dataset generated with the HILIC-MS/MS. Importantly, Men mutants have an opposite phenotype of Cyfip 85.1/+ flies, with an increase in the NADP + /NADPH ratio. In addition, reduction of Men in the Cyfip 85.1/+ background can fully rescue the NADP ratio confirming its regulation by Men (new Fig. 5a). 3) Regarding the Betulin drug provision experiments, the method of administration was monitored via consumption of the drug mixed into blue food. However, there is no quantification of how much food was digested or if the drug was found in the relevant areas of the brain. We agree with the reviewer that is difficult to know exactly the amount of food consumption. However, we suceeded to monitor and compare the consumption of food containing betulin (1mM for 48hrs), vehicle (DMSO) or water (alone) in control and Cyfip 85.1/+ flies. Food intake was assessed as previously described (Kanellopoulos et al., 2020 Cell) monitoring the absorbance at 620nm from each single fly abdomen. We could conclude that no preference/avoidance for the drug-containing food was observed between the two genotypes. This dataset has been added in the revised manuscript (new Supplementary Fig. 5c).
Supplementary Fig. 5c, Quantification of food ingestion in control (n = 10) and Cyfip 85.1/+ (n = 10) flies treated with Betulin, DMSO or water. Two-way ANOVA n.s. = not significant. Mean ± S.E.M. Figure 2b (the 24hr profile for NADP+/NADPH ratios, in mutants vs control) is key to this study. Unfortunately, the it is also one of the less believable graphs. The difference between the mutant and controls depends on one point, where significance seems marginal. That the 16hr timepoint happens to match the timepoint showing decreased nighttime sleep in the mutant could be viewed as coincidental. I wonder if there are additional approaches that could be taken to validate this result? We are very grateful to the reviewer for suggesting alternative approaches to detect the 24hr profile for NADP + /NADPH ratio in control and mutant flies. We performed targeted mass spectrometry analysis (HILIC -MS/MS) to measure the NADP ratio in fly heads every 4 hrs over 24 hrs. The mass spectrometry data is more sensitive and robust than the previously employed ELISA assay (see new Figs 2a and 5a). Importantly, we observe that in control flies the NADP+/NADPH follows the behavioural state of the fly, i.e., peaking at high wakefulness periods (ZT0 and ZT12) before sleep periods and descending at ZT16 when sleep need is reduced. In contrast, Cyfip 85.1/+ flies do not show a significant change of the NADP + /NADPH ratio (between ZT8 and ZT16) after the peak of wakefulness (ZT12) (new Fig. 2a).

4)
We propose that the NADP ratio oscillations in brain might reflect the sleep/wake behavioural state and that are relevant to induce the night-time sleep onset (model in Fig. 5d), consistently with the effect on sleep due to the increase of NADP + optogenetically induced, observed by the prof. Miesenböck's lab in the dFB circuit. We decided to replace the former  5) Additionally, regarding the immunohistochemical experiments, were brain dissections done at a specific time of the day? If SREBP levels change throughout the course of 24 hours (peak expression at ZT12-ZT16) all dissections would need to be completed at a specific set time to account for circadian variation. Whether this was accounted for is unclear.
We have now repeated the experiment and better specified in the methods section and legend that the IF in fly brain was performed at ZT12, considering therefore the circadian timing, new Fig. 4f. 6) Starvation leads to sleep loss as well; this is well documented in the field, and is obviously related to metabolism homeostatic processes as well. Have the authors excluded the possibility that they are actually describing one aspect of that well-described phenomenon? In other words, all cells might experience NADP+/NADPH ratio changes after extended wakefulness, and these might be reversed upon starvation conditions. Is it possible this has less to do with sleep than more general brain processes linked to hunger, with the mutant animals investigated here being simply more hungry at the start of the night(hence, not sleeping)? It's not clear that this has been ruled out or even considered.
We previously showed that Cyfip 85.1/+ flies do not show differences in food consumption over 24 hours or part of the daytime period (ZT0-ZT6, Kanellopoulos et al., 2020). Following the reviewer suggestion, we investigated the feeding behaviour of Cyfip mutant flies assessing food consumption, see above comment (3), during the daytime phase (ZT0-ZT12) and before night-time (ZT10-ZT12). We did not observe differences of feeding behaviour between control and Cyfip 85.1/+ flies. We have now added these datasets in the revised manuscript (new Supplementary Fig. 1h and i).

Minor concerns and suggestions:
1) Figure 1a -a Schematic would be helpful to the reader to follow experimental setup. Following the reviewer's suggestion, we have added a schematic of the Drosophila Activity Monitoring System (Trikinetics) experimental setup. (new Supplementary Fig. 1a).
Supplementary Fig. 1a, Schematic of the Drosophila Activity Monitoring (DAM) System.
2) Figure 1b -Total max of night-time sleep should be 720 minutes We thank the reviewer for this suggestion. We have now revised the y-axis scale of the night-time and daytime sleep amount with 720 minutes.
3) Figure 3 and generally seq data -Further explain the rationale behind using a cutoff fold change of +/-1.3 as the standard method is to use is Log2FC of 0.58 = LogFold of 1.5. Whilst the authors do state that this was due to a FC of 1.3 of Cyfip gene this may need to be detailed more? Figure 3b could be more informative, e.g. showing some raw seq reads. We are grateful for this suggestion. Initially we arbitrarily used as cut-off the difference in the Cyfip mRNA level between WT and Cyfip 85.1/+ . Following the reviewer's suggestion, we reanalysed the RNA seq dataset with a more stringent cut-off of Log2FC of ±0.585 (50% fold increase/decrease). Importantly, all conclusions remain valid with the new analysis. We have updated and revised  We thank the reviewer for this comment. Also following the other reviewers' advice, we improved the signal to noise ratio using an anti-GFP antibody (see methods) (new Fig. 4f). We quantified the same-dimension ROI on 3 brain areas showing a clearer GFP expression (superior lateral protocerebrum; suboesophageal ganglion and the ventrolateral protocerebrum). To account for background intensity, we subtracted an ROI of the same dimension outside the brain tissue, because any other area in the brain seems to express SREBP. activation. The transcription factor domain-encoding sequence was replaced by a Gal4-encoding sequence, rendering it specific for the UAS promotor sequence. f, Quantification of the relative GFP labelling intensity at ZT12, in control (n = 12 brains) and Cyfip 85.1/+ (n = 23 brains) flies. **p = 0,0017 by two-tailed unpaired Student's t-test. Mean ± S.E.M. Scale bar = 50 µm. In the representative figure, the max projections of the Z-stack and magnified view of the region marked by white square are presented. 5) Extended figure 2d/e -When comparing the data of 2d and 2e some disparities are seen. Cyfip knockdown in RepoGal4 looks (*) more significant than in R23e10Gal4. Some differences in panel d seem as large as in e, yet none are significant in d. This seems suspect. Could this be due to the statistical testing as the former also includes the Nrv-Gal4 dataset, so simply a problem of multiple comparisons? Secondly The UAS-Cyfip-IR controls differ between the datasets. We thank the reviewer for raising this concern therefore we replicated the experiment one more time confirming the previous results: a reduction in night-time sleep in R23E10Gal4 flies and no effect on night-time sleep in RepoGal4 flies. We have revised the figure adding the additional values (revised Suppl. Fig. 3c and Suppl. Fig. 2h). Specifically, both Cyfip RNAi lines have a significant reduction in sleep amount when crossed to the R23E10Gal4 driver (Suppl. Fig. S3), while when crossed to the RepoGal4 driver only one significant difference is detected, for RNAi line 1 compared against the no-driver control (there is no significant difference for RNAi line 2, nor for RNAi line 1 against the no-RNAi control). We conclude that knock-down of Cyfip in R23E10-positive cells reduces sleep. In contrast, RepoGal4 driven Cyfip knock-down does not. Because there are several genotypes in the dataset, we applied Sidak's multiple comparisons test. The reported significance values refer to the corrected values for multiple comparison (Fig. 1, for the reviewer only). To have an independent statistical analysis we performed One Way ANOVA excluding the NrvGal4 dataset and obtained the same results (Fig. 2 5) Finally, there is no quantification of these knockdowns. We thank the reviewer for his/her comment. We compared Cyfip mRNA levels by RT-qPCR in flies with pan-neuronal reduction of Cyfip expression (Ras2Gal4;Gal80 ts > UAS-Cyfip-IR 1 or 2 ) to controls. We observed a reduction by at least 30% of Cyfip mRNA expression levels upon the two RNAi expression. We have now added this dataset in the revised version of the manuscript (new Suppl. Fig. 2a).
Supplementary Fig. 2a, a, Quantitative RT-PCR to assess the levels of Cyfip mRNA normalized to rpl32. Ras2Gal4;TubGal80 ts/+ (n = 12), UAS-Cyfip-IR 1/+ (n = 7), Ras2Gal4;TubGal80 ts > UAS-Cyfip-IR 1 (n = 7), UAS-Cyfip-IR 2/+ (n = 7) and Ras2Gal4;TubGal80 ts > UAS-Cyfip-IR 2 (n = 7). Ordinary one-way ANOVA followed by Sidak's multiple comparison test, ****p < 0.0001, **p = 0.0018, ***p = 0.001, ****p < 0.0001. n = pool of 15 fly heads. Mean ± S.E.M. (see also Supplementary Data 6). Figure  7) Methods: Sleep-Wake activity assays -light as an arousal stimulus is unusual, as it interferes with the circadian clock. This might need some discussion, to address concerns that circadian factors aren't at play here. We thank the reviewer for this comment. We believe there is no interference on the circadian rhythm by the light stimulus because for 3 days the light cycles were regular and only the last day 3 flashes of light were given, and the experiment ended (see methods). The light stimulus in Drosophila was previously used as arousal stimulus (for example Seugnet et al., 2009, PMID: 19494137;Ni et al., 2019, PMID: 30719975) and we were inspired by these publications showing that specific circuitries regulating arousal activated by light stimuli are independent from circadian pacemaker circuitries (Sheeba et al., 2008, PMID: 18771923). We have now mentioned these papers in the result section.

6) Extended
It would also be interesting to know how many flies were not responding to this stimulus. To address this point, we have added a new panel that shows for each time point of the unexpected stimulus the number of flies responding to the stimulus (new Suppl. Fig. 1g).
Supplementary Fig. 1g, Percentage of flies showing a reduction of sleep >2% compared to baseline sleep. Shown are the data for control and Cyfip 85.1/+ flies, as well as three time points when the arousal stimulus was provided (ZT16, ZT18 and ZT20). Fisher's exact test, p = 0.0118, control vs Cyfip 85.1/+ at ZT16, n.s. at ZT18 and ZT20. 8) Fig. 5: in the concluding model (panel d) the authors seem to imply a daytime sleep effect, as well as a night time effect (increased NADP+/NADPH ratio leads to low sleep drive during both day and night). Yet, this is not what is proposed in the title and abstract and discussion. The authors might need to rethink their effects on daytime sleep, and this included showing all the daytime sleep data so to that readers can see the extent to which day and night sleep correlate in these manipulations. This is critical, because without the word 'night' in the title, the story packs somewhat less of a punch. Following the reviewer's suggestion, we have now included the sleep data during the daytime for all the experiments performed in which we observed a night-time sleep phenotype further strengthening the importance of the metabolic pathway in the regulation of night-time sleep onset and sleep need.
In the revised version of the manuscript, we have modified the model highlighting the specificity of this mechanism at the night-time sleep onset. New Fig. 5d, Model.

Reviewer #2 (Remarks to the Author):
Mariano et al. use a previously established Drosophila model for neurodevelopmental disease to investigate the molecular mechanisms underlying sleep dysregulation in these disorders. They study flies that have a 50% reduction in Cyfip, a protein implicated in various neuropsychiatric disorders. Their data suggest that Cyfip inhibits SREBP which in turn upregulates malic enzyme. Thus, a reduction in Cyfip is proposed to enhance SREBP and malic enzyme levels, which then increase the NADPH/NADP ratio, resulting in a putative decrease in the metabolic drive for sleep. In general, the work is solid, especially the links between Cyfip, SREBP, and malic enzyme, and the functional connection between lipid metabolism and sleep regulation is interesting and potentially important. However, there are questions about whether the observed behavioral phenotypes are specifically related to sleep homeostasis, which could limit the novelty of the findings.
We appreciate the reviewer's positive comments on our work and performed the suggested experiments that helped to improve our manuscript. We hope that he/she is pleased with the new datasets included in the revised version of the manuscript.

Major points:
1) The sleep phenotypes observed may not reflect defects in sleep homeostasis. For example, in Figures 1D-1E, the data show that Cyfip hets are hyperaroused, which could account for the reduced baseline sleep and decreased recovery sleep after deprivation. We thank the reviewer for the comments. We do not think that the Cyfip 85.1/+ are largely hyperaroused because after providing the light stimuli at night-time we did not observe more Cyfip 85.1/+ responders compared to control flies, that could account for the increase in arousal and reduction of arousal threshold (new Suppl. Fig. 1g). Nevertheless, Cyfip 85.1/+ flies have more troubles to fall asleep and to reach a baseline sleep level after light pulses compared to control flies (Fig. 1d).
Supplementary Fig. 1g Fig. 2b), testifying the increase in sleep need reflected by the accumulation of NADP + over NADPH while no change in the NADP + /NADPH ratio was detected in Cyfip 85.1/+ flies. Cyfip and Srebp mRNA levels did not change between noSD and SD conditions in wild-type flies (Fig. 3 for the reviewer only). 2) It is not clear that Cyfip hets lack an increase of NADP/NADPH around dusk. The data appear to show an increase, but just earlier, from ZT8 to ZT12. Also, if the NADP/NADPH ratio reflects sleep need, then one would expect the peak to be ZT12, not ZT16, since animals would be sleeping from ZT12-16, which should lower sleep need. We are very grateful to the reviewer for this comment. We have detected the NADP + /NADPH ratio in control and mutant flies using a more sensitive and robust method than the previously employed ELISA assay. Specifically, we performed targeted mass spectrometry analysis (HILIC -MS/MS) to measure the NADP ratio in fly heads every 4 hrs over 24 hrs (see new Figs 2a and 5a). Importantly, we observe that in control flies the NADP+/NADPH follows the behavioral state of the fly, i.e., peaking at high wakefulness periods (ZT0 and ZT12) before sleep periods and descending at ZT16 when sleep need is reduced. In contrast, Cyfip 85.1/+ flies do not show a significant change of the NADP + /NADPH ratio (between ZT8 and ZT16) after the peak of wakefulness (ZT12) (new Fig. 2a). Our data are indeed consistent with the hypothesis of the reviewer. We decided to replace the former figure 2a obtained using the kit Colorimetric NADP + /NADPH kit from Abcam with the new dataset generated with the HILIC-MS/MS.   Figure 4 to use ras2-Gal4, as published literature suggests that it labels both non-neuronal and neuronal cells. These experiments should be repeated with nsyb-Gal4 or elav-Gal4. Following the reviewer's comment we performed the same experiment using the ElavGal4;TubGal80 ts driver. We observed that flies expressing the driver ElavGal4;TubGal80 ts alone at 30°C show deficits in night-time sleep behaviour ( Fig. 2A and B, and Fig. 4A-B for the reviewer only) consistent with previously published work (Tomita et al., 2011. PMID: 21917797). This line is therefore not suitable for our experiment.

UAS-CYFIP RNAi2
ElavGal4;Gal80/+ ElavGal4;Gal80> UAS-CYFIP RNAi 2 UAS-CYFIP RNAi 2/+ When the nSybGal4 driver is combined with the UAS-Cyfip-IR 1/2 we did not see deficit in night-time sleep (Fig. 5, for the reviewer only). Of note, the GFP staining in nSybGal4 and Ras2Gal4;TubGal80 ts does not show a complete overlapping neuronal staining (data not shown). We therefore believe that this difference in behaviour could be due to the different expression pattern between the nSybGal4 driver and the Ras2Gal4;TubGal80 ts driver. As pointed out by the referee, while nSybGal4 has a pattern exclusively neuronal the Ras2Gal4;TubGal80 ts was described to target also some nonneuronal cells in the developing larvae (salivary glands and gut. Walker et al., 2006, PMID: 17114577). However, in the adult fly it marks the overall neurons of the CNS and it is particularly enriched in neuronal circuitries associated to learning and memory, namely the MBs (Gouzi et al., 2011, PMID: 21949657) so we are confident that we are silencing Cyfip in neuronal cells in the adult. To strengthen this potential mechanism, they should show knockdown of SREBP and malic enzyme in the ExFl2 neurons as well.
Following the reviewer's comment, that we believe meant to overexpress SREBP (same condition we have in Cyfip mutants), we overexpressed the constitutively active form of Srebp (Srebp c.del ) using the R23E10Gal4 driver. In this case, while we did not observe a significant reduction of sleep a tendency towards impaired sleep. These preliminary data suggest that SREBP alone is not enough to affect sleep-regulation in ExFI2 neurons (data not shown). Because it was shown that there is another circuitry -upstream the ExFl2 neurons -is involved in sleep homeostasis, we hypothesise that multiple neurons might be involved (Liu et al., 2016, PMID: 27212237).
Men overexpression in this circuit is also a great idea, we have looked for this line extensively but unfortunately there are no described fly overexpressing Men. We thank the reviewer again for this suggestion and we hope to generate additional specific fly lines in the future.

Minor comments:
1) Page 3, line 2, provide citation for sleep being conserved from worms to humans. We added a citation of a recent review discussing the universality of sleep as behavioural state and the recent developments supporting the conservation of neural dynamics of sleep states across phylogeny (Jaggard et al., 2021 PMID: 34583217).
2) Figure 1E, it is unusual to examine recovery sleep after sleep deprivation during the night, when sleep is already high. The authors do examine recovery sleep during the daytime after 12 hr of sleep deprivation in Figure S2. Recommend moving the panel from Figure S2 to the main figures, and Figure 1E to the supplemental figures.
Following this suggestion, we moved this experiment to the main figure (new Fig. 1e).
3) The authors should specify how many times the transgenic lines were backcrossed into their control background strain. Transgenic fly lines were backcrossed for 6 generations in the WT background strain. We have added this information in the methods section.

4) Can the authors comment on the marked expression of the SREBP reporter in ellipsoid body ring?
We thank the reviewer for raising this concern that was also raised by the other reviewer. We indeed discovered that the stock we were using had a P{ActGFP}JMR1 transgene in both wild-type and Cyfip 85.1/+ . generating GFP expression in ellipsoid bodies (Fig.6A, for the reviewer only). Therefore, we removed the P{ActGFP}JMR1 transgene present on the balancer (Fig. 6B, for the reviewer only).
The new experiment confirmed the increase in GFP expression from the SREBP-responsive reporter in the Cyfip 85.1/+ confirming the Cyfip-Srebp axis. We have replaced the figure (new Fig. 4d).  6) For tubGal80ts experiments, the authors state in the methods that they subject the flies to 29 deg for 3 days. Which days did they use for their baseline sleep recording? We are sorry that this part of the text was not clear. We have better explained how the experiments with the temperature inducible Gal80ts lines were performed in the methods section as follows: "Temperature-induced experiments were performed as follows: UAS-Cyfip-IR flies expressing Ras2Gal4;TubGal80 ts were raised at 18°C throughout their development to avoid the Cyfip developmentally lethal effect. The TubGal80 ts was induced at 29°C, 3-5 days after eclosion, for 3 days allowing the acute and strong induction of the Gal4. From day 4 onward flies were assessed for sleep behavior at 29°C or RNA extraction. To demonstrate that the UAS-Cyfip-IR is not expressed upon TubGal80 ts at 18°C, flies were raised, kept, and tested at 18°C. For the behavioural experiments involving UAS-Srebp wt and c.del , Ras2Gal4;TubGal80 ts > UAS-Srebp wt or c.del and respective control flies were raised at 25°C throughout development, kept and tested 5 to 7 days after eclosion at 25°C." 7) Figure S2E-"R23E18" should be "R23E10" Many thanks, we have corrected the typo.
8) The discussion is somewhat meandering. Recommend tightening this section. The discussion has been revised, it is shorter and more focused.

Reviewer #3 (Remarks to the Author):
By characterising the sleep profile of Cyfip haploinsufficiency mutants, Mariano and coauthors identified a novel and original mechanism underlying the regulation of sleep homeostasis in flies. Using a series of complementary and elegant experiments, the authors convincingly find that the activity of the master regulator of lipogenesis SREBP is upregulated in Cyfip mutants, causing the upregulation of lipogenic genes, and, in turn, nighttime sleep defects via an imbalance of the NADP+/NADPH ratio. These findings are highly relevant to the field. I recommend publication in Nature Communications provided that the authors address the major and minor points raised below.
We greatly appreciate the reviewer's positive comments on our work. In the revised version of the manuscript, we have followed his/her suggestions and performed the requested experiments accordingly. We belive that the new data have strenghtened the impact of our findings.

Major points:
1) Figure 2b. It looks like the NADP+/NADPH ratio oscillates in a circadian-dependent manner following the sleep pattern of the flies and not in a sleep need-dependent manner (as correctly stated in the abstract but not in the main text). Otherwise, why would the NADP+/NADPH start increasing when the flies are asleep, i.e. when sleep need is being dissipated, and not when sleep need is highest, i.e. at the end the 12-hour day period (ZT8-12)? Even though it is an interesting hypothesis. We are very grateful to the reviewer for this comment. We have detected the NADP + /NADPH ratio in control and mutant flies using a more sensitive and robust than the previously employed ELISA assay. Specifically, we performed targeted mass spectrometry analysis (HILIC -MS/MS) to measure the NADP ratio in fly heads every 4 hrs over 24 hrs (see new Figs 2a and 5a). Importantly, we observe that in control flies the NADP+/NADPH follows the behavioural state of the fly, i.e., peaking at high wakefulness periods (ZT0 and ZT12) before sleep periods and descending at ZT16 when sleep need is reduced. In contrast, Cyfip 85.1/+ flies do not show a significant change of the NADP + /NADPH ratio (between ZT8 and ZT16) after the peak of wakefulness (ZT12) (new Fig. 2a). Our findings are consistent with the hypothesis of the reviewer. We decided to replace the former figure 2a obtained using the kit Colorimetric NADP + /NADPH kit from Abcam with the new dataset generated with the HILIC-MS/MS. We observe that the NADP + /NADPH ratio is increased in control flies after sleep deprivation (new Fig. 2b), testifying the increase in sleep need reflected by the accumulation of NADP + over NADPH. No changes in the NADP + /NADPH ratio is observed in the Cyfip 85.1/+ flies. Moreover, does neuronal SREBP expression block synaptic homeostasis? This should be addressed in the paper. We thank the reviewer for this question. We assessed sleep behaviour using a constitutive active form of Srebp, that enters the nucleus activating transcription, using one of the sleep deprivation paradigms tested in our paper (6 hrs). The Ras2Gal4;Gal80 ts > UAS-Srebp c.del flies show indeed a deficit on night sleep homeostasis as shown by the last peak of sleep rebound (orange color) that is lower than the respective controls (Fig. 7 for the reviewer only). We therefore can conclude that SREBP levels have an affects the sleep homeostasis. The images shown in Figure 4d are very difficult to quantify and to interpret due to the low signal-tonoise ratio. Looking at the pictures, it seems that the fluorescence signal is higher in WT than mutant 'ring neurons' for example (it is visible from the pictures that SREBP is active in a subpopulation of ring neurons). Yet, the 'background' (or neuropil or SREBP?) signal is much higher in mutant than WT brains and quantifying this signal without correcting for background or without attributing it to neuronal expression might lead to wrong conclusions. One way to circumvent this problem would simply be to stain for GFP (instead of doing live imaging) and additionally to counterstain the neuropil with anti-Bruchpilot for example. This would not only amplify the signal and improve the signal-tonoise ratio but it would also allow to do ratiometric imaging and to correct, e.g., for background noise or antibody penetration. Without these changes, the results shown in Figure 4d are not conclusive. We thank the reviewer for raising this concern that was also raised by the other reviewers. We indeed discovered that the stock we were using had a P{ActGFP}JMR1 transgene in both wild-type and Cyfip mutants. generating GFP expression in ellipsoid bodies (Fig.6A, for the reviewer). Therefore, we removed the P{ActGFP}JMR1 transgene that was present on the balancer (Fig. 6B, for the reviewer). Importantly, the new experiment confirmed the increase in GFP expression from the SREBP-responsive reporter in the context of Cyfip 85.1/+ confirming the Cyfip-Sreb axis. We have replaced the figure (new Fig. 4d).
We understand the concerns about the quantification, and we have therefore performed additional stainings improving the signal-to-noise ratio detecting GFP with an antibody (compared to the previous images that were acquired at the confocal detecting the endogenous GFP with no signal amplification). The quantification is based on a ROI (same size) on 3 brain areas with GFP expression (superior lateral protocerebrum; suboesophageal ganglion and the ventrolateral protocerebrum). To account for background intensity, we subtracted an ROI of the same dimension outside the brain because Srebp seems to be expressed in all brain areas.
We did not use Brp as normalizer because in the past we had generated data suggesting that Brp expression is different between control and Cyfip 85.1/+ fly brain (Mariano and Bagni, unpublished). In addition, Brp expression is modulated by sleep pressure (Gilestro et al., 2005, PMID: 19342593).   4. e, Schematic representation of the Gal4-SREBP::GFP activation reporter and its activation. The transcription factor domain-encoding sequence was replaced by a Gal4encoding sequence, rendering it specific for the UAS promotor sequence. f, Quantification of the relative GFP labelling intensity at ZT12, in control (n = 12 brains) and Cyfip 85.1/+ (n = 23 brains) flies. **p = 0,0017 by two-tailed unpaired Student's t-test. Mean ± S.E.M. Scale bar = 50 µm. In the representative figure, the max projections of the Z-stack and magnified view of the region marked by white square are presented. 4) In Kanellopoulos et al, the same lab found a higher mitochondrial activity in the Cyfip mutant brain. This led to a redistribution of the GABA pool from synaptic vesicles into the mitochondria, thereby dampening GABAergic synaptic transmission, which, in turn, had severe effects on the social behaviour and locomotor activity of mutant flies. In the same paper, the authors also showed that the social deficits but not the locomotor activity could be rescued by decreasing mitochondrial activity or increasing GABA levels. I am surprised that the authors did not follow up on this finding in the context of sleep. It would be interesting to know whether similar manipulations as used in Kanellopoulos et al can also rescue the effects on nighttime sleep and sleep homeostasis observed in Cyfip mutants. If not, it might be very intriguing that the same protein might affect different types of behaviour (social behaviour and sleep) via entirely different metabolic mechanisms and possibly different neuronal substrates. We thank the reviewer for this suggestion and indeed our curiosity at the time of Kanellopoulos et al lead us to investigate if sleep as well is under the control of mitochondria metabolism. We tested sleep/wake behaviour in Aralar MI07552/+ and Cyfip 85.1 /Aralar MI07552 flies and did not observe an amelioration of night-time sleep in Cyfip 85.1 flies, suggesting that Aralar activity has a specific effect on social behaviour while sleep homeostasis is under the control of other factors such Srebp-Men.
We have now included this dataset in this revised manuscript (new Supplementary Fig. 3b). , a hallmark of cognitive defects due to sleep deprivation? Couldn't it also be that the sleep homeostasis machinery is defect, resulting in a reduction of homeostatic sleep? We apologize that this point of the discussion was misleading. We believe that Cyfip heterozygous flies have deficits in sleep homeostasis, and that the dysregulation of the NADP + /NADPH ratio is the driving force: in Fig. 1e and Supplementary 3i, after 12hrs or 6 hrs sleep deprivation, Cyfip mutants exhibit reduced sleep rebound. In new Fig. 2b we showed that Cyfip 85.1/+ flies after sleep deprivation do not show increase in NADP ratio, as it was observed in control flies sleep deprived, demonstrating that they have impairments in homeostatic sleep pressure. Further, the NADP + /NADPH ratio over 24 hrs mirrors deficits at the night-time sleep onset in Cyfip mutants. Therefore, it is quite possible that the defects in associative learning (Woo et al, 2019) are a consequence of sleep deprivation, similar to the cv-c mutants characterised in Donlea et al., 2014 (PMID: 24559676). This mutant, encoding a Rho-GTPase-activating protein, exhibits decreased sleep time and sleep rebound, memory deficits comparable to those observed after sleep loss. We added this notion to the discussion as follows: "In addition, Cyfip heterozygous flies exhibit impaired associative learning 30 , a hallmark of sleep loss, 96,97,98,99 suggesting that sleep disorders and/or chronic sleep deprivation might contribute and exacerbate the cognitive defects reported in Cyfip 85.1/+ flies." Figure 2e: third group from the left should be 'R23E10' instead of R23E18'. Thank you for highlighting this typo that has been corrected in the revised version.

1) Typo in Extended Data
2) In Extended Data Figure 2f, some, e.g., 'Mai179Gal4', but not all of the Gal4 names are written in italic characters. The same applies to other figures throughout the nomenclature. Could the authors homogenize the nomenclature? We thank the reviewer for this remark, the nomenclature is now in italic.
3) Page 12, Line 24/25: does this imply that the malic enzyme is only over-active at ZT16 or regulated in a circadian-dependent manner? Based on the previously published proteomics results it doesn't seem to be the case. It would be informative if the authors would comment on that.  Fig. Suppl. 5d) and fly models of insomnia (Seugnet et al., 2009, PMID: 19494137). Cyfip and Srebp mRNA levels did not change between noSD and SD conditions in wild-type flies (Fig. 3 for the reviewer only).
In addition, investigating the database for circadian rhythm (http://cgdb.biocuckoo.org/download.php, last update July 2022), we could not find Men protein to be under circadian rhythm regulation in brain.  (2019). The authors should specify that. We thank the reviewer for this remark, this aspect has been specified in the discussion. 5) Page 13, line 21/22: 'supporting the idea that lipid synthesis and remodeling is important during sleep, ..'. If so, then why do Cyfip mutants sleep less despite an upregulation of genes involved in lipid synthesis? What do the authors speculate? We agree with the reviewer's point which indeed merits a discussion. Sleep restriction and sleep deprivation have been shown to affect lipid profiles at the level of transcriptome and metabolome in mice and humans. These findings, supporting the idea that lipid synthesis and remodelling is relevant during sleep to restore the metabolic pool used for brain activity during wakefulness. Our hypothesis is that increased expression of genes involved in energy metabolism and lipid synthesis during the day affects the homeostatic sleep regulation in Cyfip mutant flies presumably reducing the homeostatic pressure at the night onset.

Reviewer #4 (Remarks to the Author):
In this manuscript, Mariano et al provide an interesting and thorough description of a sleep phenotype associated with the Cyfip gene and its epistatic pathway. The authors show that cyfip mutant heterozigous flies have a short-sleep nocturnal phenotype and possible homeostatic misregulation and they propose that upregulation of SREBP and Men are responsible for this phenotype.
The work features an impressive amount of work, generally well-controlled and well presented. I personally do not like the overly translational approach in the manuscript, insisting over and over again on possible links with human disease that may or may not exist; I think the manuscript ultimately suffers from adopting this approach and the findings end up being secondary but I recognise this may be the authors' style and they are entitled to use whichever style they prefer.
Overall, I think the work is solid and self-standing and I do not have any requests for further experiments. I only have some minor suggestions/requests mostly regarding data presentation and wording of the conclusions: We appreciate the reviewer's positive comments on our work. In the revised version we have followed his/her suggestions and performed the requested experiments.
1) The term haploinsufficient refers to genes, not to animals. The use of "haploinsufficient flies" (e.g. line 3 pg5) is technically inappropriate. The flies are heterozygous for the gene mutation whilst the gene is haploinsufficient. We thank the reviewer for this important remark. We have now replaced the term haploinsufficient with heterozygous in the revised manuscript.
2) An EEG/MRI abnormality is not a "sleep disturbance" (line 12 pg 4). It may in some cases correlate with one but a change in EEG pattern is not a disturbance per se. We this important comment and have now removed the citations referring to EEG/MRI abnormalities that did not describe sleep deficits and left the references that describe insomnia and sleep disorders in these patients.
3) In the figures, please add more information regarding the number of animals used.  fig. 2 and 5. I am just quite surprised that a change in enzymatic activities in only a few neurons can be picked up doing biochemical assays in the whole brain. We understand the reasoning of having the expression pattern of Cyfip in the entire brain becauseas of today -it has not been shown in the adult brain. Unfortunately, there are no good antibodies to detect the endogenous CYFIP protein. We have tried to have them produced by 21 st Century and the result is not compelling. We therefore opted for the generation of transgenic fly with a tagged version of CYFIP using the CRISPR-Cas9 technology in which the endogenous CYFIP has a HAtag at the N terminus. Immunostaining for HA (in green) and for nc82 (anti-Brp, pre-synaptic marker) (in magenta) revealed that CYFIP N-HA in expressed in most of the brain regions and at synapses (new Suppl. Fig. 1l).
Supplementary Fig. 1l, Representative pictures of whole brain immunohistochemistry of CYFIP N-HA flies for anti-HA (green), anti-BRP (nc82) (purple) and merge. Scale bar = 50 µm. 7) Please provide more details regarding the statistical analysis used to study the overlap of genes shown in fig. 3 and discussed on pg 9. A hypergeometric distribution is mentioned in the figure legend without further details. We thank the reviewer for these comments. We have now added in the methods section a sentence stating that the hypergeometric distribution analysis in the RNA-seq datasets was performed using R (https://stat.ethz.ch/R-manual/R-devel/library/stats/html/Hypergeometric.html) and the exact pvalue in the result section.
Was the same analysis done for the data in figure 4a? with what significance? The same hypergeometric distribution analysis was indeed also performed for Fig. 4a. In this context, we obtained a p-value of 0.98 because even if the overlap is for 129 genes, it is less than 10% (129 genes from 1303 and 1366) and not significant. Next, we performed a new analysis reasoning on which genes of the SREBP-overexpression datasets are relevant to wakefulness (as we did in Fig.  3e for the Cyfip mut dataset). Here we identified a subset of SREBP-regulated genes associated to wakefulness (21 genes, new Supplementary Data 5). When comparing the wakefulness associated genes dysregulated in Cyfip 85.1/+ and in the SREBP-OE we identified 10 genes (new Supplementary  Table 1). The hypergeometric distribution analysis on the overlap of these 2 datasets reveals a significant p-value (p = 3.467 -21 , new Fig. 4b), consistent with all the biological observations in this work.  fig. 5c and 5b. While suggestive, I am not convinced this is enough evidence for such a definitive claim. I recommend using a more cautious approach in your conclusions. We agree with reviewer's comment that is important to further validate the link between NADP + /NADPH and Men. We performed targeted mass spectrometry to detect with higher sensitivity the NADP ratio in Men mutant flies. Importantly, Men mutants show an opposite phenotype of Cyfip het flies, with increase NADP + /NADPH (new Fig. 5a), and increased night-time sleep (new Fig. 5c). In addition, abrogation of Men in the Cyfip 85.1/+ background can fully rescue the NADP ratio. These data confirm that Men modulation affects NADP ratio and night-time sleep according to our model. We decided to replace the former figure 5a obtained using the kit Colorimetric NADP + /NADPH kit from Abcam with the new dataset generated with the HILIC-MS/MS. 9) On the same line: please amend the title to be more accurate in its description. "drives" and "control" are two very strong words for something that affects only a relatively small part of the phenotype. We thank the reviewer for this comment, we modified the title of the manuscript as: "SREBP modulates the NADP + /NADPH cycle to control night-time sleep"

8) The epistatic experiments shown in fig. 5 are very nice but the only evidence that Men is involved with this process is coming from the one experiment shown in
The authors have done an excellent job addressing all of the reviewer comments. They provide a substantial amount of new data and reanalysis, which has now made their work more convincing. It was also good to see consistency among the different reviews, and that the authors went out of their way to address every single point thoroughly.
I have only two remaining suggestions, that the authors and editors can decide how to handle.
1. My suggestion for a schema up front in Figure 1 was not in relation to Trikinetics hardware implementation, which is trivial. Rather, it related to placing the molecule in question in some cellular pathway already, schematically. It is often hard for the average reader to jump straight into sleep profile data involving mutant acronyms, and it does help to at least have some idea of the biology at stake, visually. This might be a membrane schema with the multiple players involved, including the first proteins of interest, and how they interact. Why should we be interested in this, and can we already imagine a consequence (on sleep) of mutating these proteins? Try to provide this visually, up front.
2. The authors now provide most of the daytime sleep data as requested, to compare with nighttime sleep. Thank you. It would however be a missed opportunity if the authors don't provide a little more discussion as to why there might be such a dichotomy, beyond the referenced observation that arousal thresholds are different. Why might nighttime sleep be qualitatively different? Are different functions being served? How might this force us to reconsider how the field studies sleep in this model? Are metabolic processes not relevant for daytime sleep? I recommend the authors provide some interesting discussion here, beyond just stating that they are different.
Reviewer #2 (Remarks to the Author): In this revised manuscript, the authors perform a significant number of new experiments, adding new data and replacing some of the original data. Although their model connecting Cyfip -> lipid metabolism -> SREBP/MEN -> NADP/NADPH -> sleep pressure continues to be interesting, there remain concerns regarding whether the experimental data adequately support this model. Fig. 2a, the authors use a new approach (HILIC-MS/MS) to quantify the NADP/NADPH ratio across time. However, the curves shown are not clearly linked to sleep pressure. For example, in control flies, the NADP/NADPH ratio decreases across the day (except for the small peak at ZT12) and increases across the night when flies should be sleeping. The authors claim that reduced sleep pressure around ZT12 is due to the small NADP/NADPH peak at ZT12 being lost in Cyfip heterozygotes. However, there is a greater difference at ZT0-according to their argument, wouldn't there also be a reduction in sleep at ZT0 in Cyfip heterozygotes? The more likely explanation is that NADP/NADPH is a downstream marker of increased locomotor activity.

In new
2. Re: Figure 1d, the authors argue that the differences in sleep lost following light pulses are not due to changes in arousal threshold because similar or lower numbers of Cyfip heterozygotes exhibit a >2% reduction in sleep following these stimuli. While the authors may ultimately be correct, it is still difficult to definitively rule out changes in arousal threshold without more experimentation. First, most researchers use any awakening as the criteria to define arousal threshold. Second, if the authors choose not to use that criterion, they should perform a careful analysis of different "arousal thresholds" to more clearly demonstrate that arousal threshold is not affected.
3. There remains concern about imprecision about the relevant circuits. The authors use Ras2-Gal4, which is known to have non-neuronal expression, but claim that in adult flies Ras2-Gal4 is exclusively expressed in neurons. They cite Gouzi, 2011 to support this claim, but I didn't find any evidence in that paper that Ras2-Gal4 is only expressed in neurons in adult flies? Instead, Gouzi 2011 cites Walker, 2006, which in turn cites Salzberg, 1993, and Salzberg 1993 describes expression in the adult reproductive system. Thus, based on that observation, Ras2-Gal4 is not strictly pan-neuronal in adult flies. They are unable to reproduce their Cyfip knockdown phenotype using nsyb-Gal4 and claim that ras2-Gal4 and nsyb-Gal4 are not perfectly overlapping in their neuronal expression, but do not provide these data for the reviewers. In addition, there are other pan-neuronal drivers that could be used such as R57C10-Gal4. In light of their inability to find a difference using SREBP or MEN overexpression with R23E10-Gal4, conclusively demonstrating that Cyfip acts in neurons would seem to be essential. Fig. 5a, the authors show genetic interactions between Cyfip heterozygotes and SREBP and MEN alleles and use these data to argue that the NADP/NADPH ratio is "rescued." However, there is concern that the interactions shown are simply additive, and thus lack specificity. Cyfip heterozygotes exhibit a reduced NADP/NADPH ratio while reduction of SREBP or MEN on their own results in an increase in NADP/NADPH ratio; when combined, the transheterozygotes exhibit an intermediate phenotype. In other words, if one were to take any random genetic manipulation that led to an increase of NADP/NADPH ratio, it is possible that they would also "rescue" the reduced NADP/NADPH ration seen in Cyfip heterozygotes. Figure S5d, they show that Men transcript levels rise with sleep deprivation. However, according to their model, if Men acts upstream as part of the signaling mechanism for sleep pressure, then one would expect that Men levels would be reduced with sleep deprivation. Instead, the increased Men levels (which should reduce NADP/NADPH ratio and lower sleep pressure) appear to be a downstream compensatory response, consistent with their NADP/NADPH timecourse data.

In
Minor comments: 1. There is awkward language and minor errors in the manuscript, and the text would benefit from careful editing. For example, line 139, "5 min of light pulse." Line 141 "loose". Line 313, "The malic enzyme pairs SREBP to sleep behavior." Line 339, "3 key aspects" but then they list 4 aspects. Line 119, unnecessary comma after "SREBP activity."

Figures S3e and S3f
, the activity traces in LD look remarkably "clean." Also, if one were to estimate sleep based on those activity traces, they would not seem to correspond to the sleep data shown in Having reviewed the responses given by the authors to my comments -and to the comments of the other 3 reviewers -I believe the manuscript is now improved and I have no further comments or suggestions.

Mariano et al. NCOMMS-21-46266-T "SREBP drives the NADP+/NADPH cycle to control night sleep".
We would like to thank the reviewers for their positive feedback supporting publication of our manuscript in Nature Communications. We have also taken the additional comments of the reviewers into consideration and provide additional data in support of our model. We hope that the current revised version will be suitable for publication.

REVIEWER COMMENTS
Reviewer #1 (Remarks to the Author): The authors have done an excellent job addressing all of the reviewer comments. They provide a substantial amount of new data and reanalysis, which has now made their work more convincing. It was also good to see consistency among the different reviews, and that the authors went out of their way to address every single point thoroughly. We really thank the reviewer for appreciating the extensive work we did to address the relevant comments we received on our manuscript.
I have only two remaining suggestions, that the authors and editors can decide how to handle. Figure 1 was not in relation to Trikinetics hardware implementation, which is trivial. Rather, it related to placing the molecule in question in some cellular pathway already, schematically. It is often hard for the average reader to jump straight into sleep profile data involving mutant acronyms, and it does help to at least have some idea of the biology at stake, visually. This might be a membrane schema with the multiple players involved, including the first proteins of interest, and how they interact. Why should we be interested in this, and can we already imagine a consequence (on sleep) of mutating these proteins? Try to provide this visually, up front. We understand the suggestion of the reviewer and thought extensively how to make a scheme. At the end we felt that the concept we developed had an important overlap with the graphical abstract so we would like to keep the graphical abstract only.

My suggestion for a schema up front in
2. The authors now provide most of the daytime sleep data as requested, to compare with nighttime sleep. Thank you. It would however be a missed opportunity if the authors don't provide a little more discussion as to why there might be such a dichotomy, beyond the referenced observation that arousal thresholds are different. Why might nighttime sleep be qualitatively different? Are different functions being served? How might this force us to reconsider how the field studies sleep in this model? Are metabolic processes not relevant for daytime sleep? I recommend the authors provide some interesting discussion here, beyond just stating that they are different. We would like to thank the reviewer for this comment. We have now expanded on a few concepts in the discussion. Specifically, on pg 15 we state: "Notably, night-time and daytime sleep features differ in flies 81 . Brain activity, measured as local field potential (LFP) and the responsiveness to stimuli during night compared to daytime sleep, suggesting different levels of homeostatic pressure for these processes along the 24 hrs 82,83 . While these differences have been reported, the function of daytime and night-time sleep in Drosophila remains unclear, although some hypotheses point to memory consolidation and synaptic homeostasis 82,83 . Therefore, the identification of factors, as Cyfip, regulating differentially daytime and night-time sleep helps to shed light on the characteristics of these temporally distanced sleep. Only few genetic factors and mechanisms have been so far identified as regulators of daytime and night-time sleep, for instance hormones, immune response, oxidative stress and lipid binding molecules 81 ."

Reviewer #2 (Remarks to the Author):
In this revised manuscript, the authors perform a significant number of new experiments, adding new data and replacing some of the original data. Although their model connecting Cyfip -> lipid metabolism -> SREBP/MEN -> NADP/NADPH -> sleep pressure continues to be interesting, there remain concerns regarding whether the experimental data adequately support this model. We would like to than the reviewer for finding the link CYFIP-NADP/NADPH interesting. We hope that with the additional experiments added in this additional revision we successful convince him/her about our model. Fig. 2a, the authors use a new approach (HILIC-MS/MS) to quantify the NADP/NADPH ratio across time. However, the curves shown are not clearly linked to sleep pressure. For example, in control flies, the NADP/NADPH ratio decreases across the day (except for the small peak at ZT12) and increases across the night when flies should be sleeping. The authors claim that reduced sleep pressure around ZT12 is due to the small NADP/NADPH peak at ZT12 being lost in Cyfip heterozygotes. However, there is a greater difference at ZT0-according to their argument, wouldn't there also be a reduction in sleep at ZT0 in Cyfip heterozygotes? The more likely explanation is that NADP/NADPH is a downstream marker of increased locomotor activity. We thank the reviewer for this comment. We believe that -in our experimental conditions -the NADP + /NADPH oscillation is not a merely downstream marker of increased locomotor activity. This conclusion is based on the following experiment: we quantified the locomotion amount (beam crossing quantification) in control and Cyfip heterozygous flies at ZT0 and ZT12, the moment where the flies show the highest activity -and we did not observe any differences between control and Cyfip heterozygous flies. In addition, if NADP + /NADPH would be a downstream marker of increased locomotor activity we would have not observed differences in locomotion between ZT8, ZT12 and ZT16 in Cyfip heterozygous flies, as the NADP + /NADPH is not oscillating between these 3 time points in Cyfip heterozygous flies ( Figure 1 for the reviewer). In addition, in Figure 2a we don't link the observed pattern with homeostasis sleep pressure but we speculate that the ratio NADP + /NADPH reflects the behavioral state of the fly, i.e., peaking at high wakefulness periods (ZT0 and ZT12) before sleep initiation and descending at ZT16 when sleep need is gradually reduced and sleep behavior increases (Fig. 2a). The experiment that shows that NADP+/NADPH is linked to homeostatic sleep pressure is summarized in Fig. 2b in which, following a gold standard protocol, we show that NADP + /NADPH is increased at sleep deprivation.

In new
2. Re: Figure 1d, the authors argue that the differences in sleep lost following light pulses are not due to changes in arousal threshold because similar or lower numbers of Cyfip heterozygotes exhibit a >2% reduction in sleep following these stimuli. While the authors may ultimately be correct, it is still difficult to definitively rule out changes in arousal threshold without more experimentation. First, most researchers use any awakening as the criteria to define arousal threshold. Second, if the authors choose not to use that criterion, they should perform a careful analysis of different "arousal thresholds" to more clearly demonstrate that arousal threshold is not affected. We thank the reviewer for these suggestions, and we performed a new analysis of the data relative to the arousal experiments using the awakening as criteria to define the not responder and responder flies. In this new analysis flies were divided in "responders" flies with no activity 5 min before the stimulus and exhibiting beam crossings within 5 min after the light pulse" and "not responders": flies with no activity 5 min before the stimulus and not exhibiting any response withing 5 min after the light pulse (as in Kayser et al., 2014, Science PMID: 24744368) (Figure 2 for the reviewer). Statistical analysis (Fisher's exact test, between "responders" and "not responders" at ZT16, ZT18 and ZT20 in control and Cyfip 85.1/+ flies did not reveal differences between the 2 genotypes. Therefore, we conclude that the Cyfip 85.1/+ are not largely hyper-aroused because after providing the light stimuli at night-time we did not observe more Cyfip 85.1/+ responders compared to control flies. Figure 2 for the reviewer: Number of "responding" flies showing waking response after light stimulus and "not responding" flies that did not respond to light stimuli. Shown are the data for control and Cyfip 85.1/+ flies at three time points when the arousal stimulus was provided (ZT16, ZT18 and ZT20). Fisher's exact test between responding and not responding flies in control and Cyfip 85.1/+ at ZT16, ZT18 and ZT20, n.s.

Criteria:
Awake: flies that are moving in the 5 minutes before the stimulus Not responding: flies that were not moving in the 5 minutes before the stimulus and that did not moved in the 5 min after the stimulus Responding: flies that were not moving in the 5 minutes before the stimulus and that moved whithin the 5 minutes after the stimulus Fisher's exact test between not responding and responding flies at ZT16, ZT18 and ZT20 = n.s.

3.
There remains concern about imprecision about the relevant circuits. The authors use Ras2-Gal4, which is known to have non-neuronal expression, but claim that in adult flies Ras2-Gal4 is exclusively expressed in neurons. They cite Gouzi, 2011 to support this claim, but I didn't find any evidence in that paper that Ras2-Gal4 is only expressed in neurons in adult flies? Instead, Gouzi 2011cites Walker, 2006, which in turn cites Salzberg, 1993, and Salzberg 1993 describes expression in the adult reproductive system. Thus, based on that observation, Ras2-Gal4 is not strictly pan-neuronal in adult flies. They are unable to reproduce their Cyfip knockdown phenotype using nsyb-Gal4 and claim that ras2-Gal4 and nsyb-Gal4 are not perfectly overlapping in their neuronal expression, but do not provide these data for the reviewers. In addition, there are other pan-neuronal drivers that could be used such as R57C10-Gal4. We thank the reviewer for this comment that we have taken into consideration. We cited Gouzi et al., 2011 as they used the Ras2-Gal4 to drive their gene of interest in the adult CNS. We are aware that at the larval stage the Ras2 is also expressed in salivary glands, guts, central brain region and ventral nerve cord (Saltzberg et al., 1993;Walker et al., 2006). We have therefore revised the text as follows "We used the neuronal Ras2Gal4 driver, coupled with TubGal80 ts to specifically avoid lethal effects of Cyfip abrogation during larval development 56 , that is largely expressed in the overall neuronal population of adult fly CNS 62 , although not exclusively during larval development 63,64 ." mentioning for the reader that the Ras2-Gal4 is not exclusively pan-neuronal in larval flies, since it targets neurons but also non-neuronal cells in the body of the fly.
We now show that the expression pattern of nSyb-Gal4 and the Ras2-Gal4 drivers is not completely overlapping.
As an example, in the nSyb-Gal4 flies we have observed cells that are Elav+ and GFP-in the region around the antennal lobes ( Figure 3A for the reviewer) marked by the white arrows (2 independent representative images) suggesting that nSyb is not expressed in all neuronal cells ( Figure 3B). In addition, in the nSyb-Gal4 flies we observed cells that are GFP+ and Elav-(marked by the yellow arrow) ( Figure 3B).
As an additional example suggesting a non 100% overlapping pattern is shown in Figure 3C.
In the Ras2-Gal4 the group of cells (around the antennal lobe) are all Elav+ and GFP+ ( Figure  3C) suggesting that nSyb is expressed in all neuronal cells here analyzed.
We can conclude that Ras2-Gal4 in adult flies targets neurons with a pattern that is not 100% overlapping with the nSyb-Gal4 driver. Figure 3 for the reviewer: A. Graphic of the Drosophila brain showing pan-neuronal labeling (red dots depict cell nuclei). The square black box correspond to the regions analyzed by confocal in B and in C (nSyb-Gal4> UAS-mCD8::GFP and Ras2-Gal4> UAS-mCD8::GFP respectively) for anti-Elav (in red) and anti-GFP (in green). AL: Antennal lobe, MB: mushroom body. White arrows point to Elav+ and GFP-cells and the yellow arrow to a cell GFP+ and Elav-cell. Scale bar = 50um.
In light of their inability to find a difference using SREBP or MEN overexpression with R23E10-Gal4, conclusively demonstrating that Cyfip acts in neurons would seem to be essential. We thank the reviewer for this suggestion. While monitoring Men overexpression in this circuit is a great suggestion, unfortunately a strain with mutations in Men is not available and the generation of additional specific fly lines will be considered for future studies.
4. In Fig. 5a, the authors show genetic interactions between Cyfip heterozygotes and SREBP and MEN alleles and use these data to argue that the NADP/NADPH ratio is "rescued." However, there is concern that the interactions shown are simply additive, and thus lack specificity. Cyfip heterozygotes exhibit a reduced NADP/NADPH ratio while reduction of SREBP or MEN on their own results in an increase in NADP/NADPH ratio; when combined, the transheterozygotes exhibit an intermediate phenotype. In other words, if one were to take any random genetic manipulation that led to an increase of NADP/NADPH ratio, it is possible that they would also "rescue" the reduced NADP/NADPH ration seen in Cyfip heterozygotes.
The involvement of Men was identified from the unbiased RNA-seq data and the involvement of SREBP derived by the list of dysregulated mRNAs -targets of SREBP -that we found in the RNA-seq data.
While we have identified SREBP and Men as key players acting on the NADP ratio to well rescue/ameliorate Cyfip mutants sleep deficits, we do not exclude the involvement of other players.
Of note, a network of 4 genes maintains the NADP + /NADPH balance and supply reducing power for lipogenesis and antioxidation (Merrit 2009): the cytosolic malic enzyme (MEN), the cytosolic isocitrate dehydrogenase (IDH), and the two oxidative enzymes of the pentose shunt, glucose-6-phosphate dehydrogenase (G6PD) and 6-phosphogluconate (6PGD). In Cyfip heterozygous condition MEN is the one that appears significantly dysregulated. Therefore, we focused specifically on this enzyme. Even if there are other molecules that can affect the NADP/NADPH ratio and modulate sleep, our conclusions won't not be affected. Figure S5d, they show that Men transcript levels rise with sleep deprivation. However, according to their model, if Men acts upstream as part of the signaling mechanism for sleep pressure, then one would expect that Men levels would be reduced with sleep deprivation. Instead, the increased Men levels (which should reduce NADP/NADPH ratio and lower sleep pressure) appear to be a downstream compensatory response, consistent with their NADP/NADPH timecourse data.

In
We thank the reviewer for raising this point. We have observed that in control flies the NADP+/NADPH increases upon sleep deprivation (initial submitted Figure 2b), the same occurs for Men mRNA transcript (initial submitted Figure S5d).
Following the reviewer suggestion, we assessed Men activity in control and Cyfip heterozygous flies during sleep (noSD) and after sleep deprivation (SD) using the same protocol to assess NADP + /NADPH and Men mRNA levels (submitted Figure 2b, S5d). In control flies, we did not observe any change in Men activity after sleep deprivation, while an increase in Men activity is observed in Cyfip heterozygous flies ( Figure 4 for the reviewer) consistent with the deficit in the NADP + /NADPH ratio (submitted Figure 2b).
Since Cyfip is a translational repressor, we hypothesized that Men mRNA translation could be under translational regulation by Cyfip. A follow up study could explore such a possibility identifying Cyfip mRNA targets and in condition of sleep and sleep deprivation. We believe addressing this point is beyond what we perceive to be the scope of the current work.

Minor comments:
1. There is awkward language and minor errors in the manuscript, and the text would benefit from careful editing. For example, line 139, "5 min of light pulse." Line 141 "loose". Line 313, "The malic enzyme pairs SREBP to sleep behavior." Line 339, "3 key aspects" but then they list 4 aspects. Line 119, unnecessary comma after "SREBP activity." We have carefully revised the manuscript. We hope that the awkward language has now been corrected.
2. "Fig 3 only for reviewers" on the top of page 14 of the rebuttal, should be provided in its entirety in the supplemental info. We thank the reviewer for this suggestion. We have now added Fig. 3 for the reviewer in the manuscript as Supplementary figure 5e and 5f.
3. Re: the GFP measurements in Figures 4e and f, usually quantification is more linear when using native fluorescence? We thank the reviewer for this remark, however even if the range was not linear, the difference between control and mutant remains valid. In addition, all samples (controls and mutants) have been processed at the same time, with the same reagents and solutions and acquired at the same time using the same confocal settings. Men Activity (OD 340 /min x ug protein normalized over noSD)

Figures S3e and S3f
, the activity traces in LD look remarkably "clean." Also, if one were to estimate sleep based on those activity traces, they would not seem to correspond to the sleep data shown in Figure 1a?
We thank the reviewer for giving us the possibility to clarify this point. The software FaasX (prof. F. Rouyer's lab -CNRF) was used to produce the actograms in Figure S3e and the period analysis in Figure S3f. Different cutoff of hash density (HD) (based on the n of movement of the fly to produce a hash mark on the actogram) can be chosen in the setting to filter the levels of activity in the actogram. Reducing the cutoff, more noise is introduced. This is evident if we compare the Figure S3e with the same actogram with a lower HD (right panels) ( Figure 5 for the reviewer). In addition, in the Cyfip heterozygous condition the moments of higher activity, in light-dark condition, are further extended in the dark phase (red squares), a sign that they are active for longer periods compared to controls indicating a decrease in sleeping during this period. I would like to thank the authors for addressing my comments and other Reviewer's comments. The revision significantly improved the manuscript, and I would like to recommend the revised version for publication at Nature Communications. We would like to thank the reviewer for his/her positive comments, and we are pleased that he/she appreciated our revised work. Having reviewed the responses given by the authors to my comments -and to the comments of the other 3 reviewers -I believe the manuscript is now improved and I have no further comments or suggestions. We would like to than the reviewer for his/her positive comments and we are pleased that he/she appreciate our revised work.
I would first like to emphasize that I am sympathetic to the substantial efforts the authors have made during the revision process. Moreover, I am not in favor of a manuscript having to go through multiple rounds of revision. Nonetheless, there remain substantive issues to address, which given the points above, I suggest should be resolved by including text that acknowledges caveats and limitations to the study.
Comment 1: The authors rebut the concern that changes in locomotor activity drive the changes in NADP/NADPH ratio by arguing that there is no difference between controls and Cyfip hets in terms of locomotor activity (despite differences in NADP/NADPH ratio) and further argue that they don't see changes in NADP/NADPH ratio at ZT8, ZT12, and ZT16 in Cyfip hets despite significant differences in locomotion.
The problem with this argument is that Cyfip itself affects NADP/NADPH ratios, so one cannot clearly examine the relationship between locomotion and NADP/NADPH ratios in these animals. Instead, if one examines control animals, the NADP/NADPH ratio follows the locomotor activity pattern reasonably well. The authors next argue that they see an increase in NADP/NADPH ratio with nighttime sleep deprivation for 8 hrs and claim this demonstrates the NADP/NADPH ratios are changing with sleep need. The potential issue with this claim is that their sleep deprivation is driving intense locomotor activity. To disentangle the effect of sleep loss vs locomotor activity in this experiment, the authors could have performed sleep deprivation during the day, which would have resulted in a similar increase in locomotor activity and affect sleep to a much lower degree. In the absence of performing additional experiments, the authors should clearly state in the text that NADP/NADPH ratios do not follow sleep need under baseline conditions (where it is instead associated with arousal or locomotor activity) and acknowledge, despite their SD experiment, that the NADP/NADPH changes might be related to increased locomotion.
Comment 2: Using a more traditional measure of arousal threshold, the authors now show that nearly all flies in control and mutant groups respond to the stimulus. Based on these data, the authors cannot claim that there are no differences in arousal threshold between controls and Cyfip hets. In other words, if one uses a very strong stimulus that arouses essentially all flies, one lacks any sensitivity to detect differences in arousal threshold. The correct way to perform these experiments is to use sub-maximal stimuli, where a minority or subsets of animals respond and show no differences between control and mutant. The authors should be careful to tone down any claims in the text of a lack of differences in arousal threshold. heterozygotes. These new data argue that MEN is NOT normally involved in homeostatic regulation of sleep, but instead is pathologically upregulated in Cyfip heterozygotes which could explain downstream effects and phenotypes. The authors should put the MEN activity in the manuscript, as these data are more relevant than showing transcript level changes, which could have no functional consequences (and indeed, the authors appear to show that this is the case).

Minor Comment 5:
Please make sure to provide information in the methods that would allow readers to understand why the activity traces look that way.
Reviewer #3 (Remarks to the Author): I would like to thank the authors for addressing my comments and other Reviewer's comments. The revision significantly improved the manuscript and I would like to recommend the revised version for publication provided they address the minor typos stated below:  Supplementary Figure 1g is misleading. In addition to 'Responders/total' the authors should also plot 'Responders/(Responding + Not responding)', thereby only taking into account awakenings from sleep, especially given the fact that the mutants sleep less during nighttime.
-Legend title of Supplementary Fig. 4 does not fit with content of figure. -> Change to, e.g., SREBP modulates sleep? -Typo in Supplementary mutants showed a reduction by approximately 50% of baseline sleep over the three time points, thus remaining awake for a longer time (Fig. 1d), suggesting a state of increased arousal.
Comment 3: The authors provide some staining images to argue that nsyb-Gal4 does not cover all neurons and likely differs in its expression pattern from ras2-Gal4. These data are not very persuasive-are the authors claiming that the small number of neurons not covered by nsyb-Gal4 but are present in Ras2-Gal4 are responsible for their Cyfip-related phenotype? Ras2-Gal4 is not a commonly used driver to express broadly in neurons. It would be much more convincing to provide data using another pan-neuronal driver such as R57C10-Gal4. In the absence of this, the authors should at least acknowledge the possibility in the text that Cyfip may be required in non-neuronal tissues for their phenotype.
We thank the reviewer for his comments. We have revised the text and acknowledged the possibility that Cyfip might be required in also in non-neuronal tissues for its phenotype as follows: Since the Ras2Gal4 driver is not exclusively neuronal 63, 64 , CYFIP might be required also in non-neuronal tissue to regulate night-time sleep behaviour.

Comment 4:
The authors argue that they identified Men and SREBP in an unbiased manner and that they are not claiming that other factors are not involved in NADP/NADPH ratio. While this is true, it does not resolve the issue that their "rescue" of NADP/NADPH ratios using Cyfip heterozygotes and SREBP and MEN alleles may be non-specific. The authors should remove the word "rescue" throughout the text, which implies that these molecules are acting in the same genetic pathway and replace it with words like NADP/NADPH ratios can be "increased" or "enhanced." We have now revised the text according to the reviewer's suggestions.
Comment 5: The authors now provide MEN activity data in the rebuttal, but not the manuscript itself, showing that in controls, MEN activity does not change with SD, whereas MEN activity is increased with SD in Cyfip heterozygotes. These new data argue that MEN is NOT normally involved in homeostatic regulation of sleep, but instead is pathologically upregulated in Cyfip heterozygotes which could explain downstream effects and phenotypes. The authors should put the MEN activity in the manuscript, as these data are more relevant than showing transcript level changes, which could have no functional consequences (and indeed, the authors appear to show that this is the case).
We thank the reviewer for this suggestion, we have now included this experiment in the manuscript as Supplementary Figure 5h and i. The text now reads as follows: Notably, despite the increase of Men transcript upon sleep deprivation in control flies, we did not observed changes in Men activity ( Supplementary Fig. 5h). On the contrary Men activity results increased, upon sleep deprivation, in Cyfip heterozygous flies ( Supplementary Fig. 5i). This is in line with the previously observed deficits in the NADP+/NADPH ratio after sleep deprivation in Cyfip85.1/+ flies (Fig. 2b) and further underlines that the pathological upregulation of Men drives changes in the NADP+/NADPH ratio and sleep deficits of Cyfip heterozygous flies.
On addition, in the discussion we state: Notably, a key player in regulating the NADP+/NADPH balance is the malic enzyme, which catalyses the conversion of cytosolic malate in pyruvate, reducing NADP+ at NADPH. Men expression and activity is pathologically upregulated in Cyfip85.1/+ flies, resulting in the impaired NADP+/NADPH and sleep. Similar to Men, dysregulation of other enzymes involved in NADP+/NADPH homeostasis might contribute to sleep disorders.